Synthetic RNA-Based Immunomodulatory Gene Circuits for Cancer Immunotherapy

Strategies for effectively modelling promoter-driven gene expression using transfer learning

The ability to deliver genetic cargo to human cells is enabling rapid progress in molecular medicine, but designing this cargo for precise expression in specific cell types is a major challenge. Expression is driven by regulatory DNA sequences within short synthetic promoters, but relatively few of these promoters are cell-type-specific. The ability to design cell-type-specific promoters using model-based optimization would be impactful for research and therapeutic applications. However, models of expression from short synthetic promoters (promoter-driven expression) are lacking for most cell types due to insufficient training data in those cell types. Although there are many large datasets of both endogenous expression and promoter-driven expression in other cell types, which provide information that could be used for transfer learning, transfer strategies remain largely unexplored for predicting promoter-driven expression. Here, we propose a variety of pretraining tasks, transfer strategies, and model architectures for modelling promoter-driven expression. To thoroughly evaluate various methods, we propose two benchmarks that reflect data-constrained and large dataset settings. In the data-constrained setting, we find that pretraining followed by transfer learning is highly effective, improving performance by 24-27%. In the large dataset setting, transfer learning leads to more modest gains, improving performance by up to 2%. We also propose the best architecture to model promoter-driven expression when training from scratch. The methods we identify are broadly applicable for modelling promoter-driven expression in understudied cell types, and our findings will guide the choice of models that are best suited to designing promoters for gene delivery applications using model-based optimization. Our code and data are available at https://github.com/anikethjr/promoter_models.

CRISPR-based gene expression platform for precise regulation of bladder cancer

The development of compact CRISPR systems has facilitated delivery but has concurrently reduced gene editing efficiency, thereby limiting the further utilization of CRISPR systems. Enhancing the efficiency of CRISPR systems poses a challenging task and holds significant implications for the advancement of biotechnology. In our work, we report a synthetic dual-antibody system that can stably exist in the intracellular environment, specifically inhibiting the functions of NF-κB and β-catenin. This not only elevates the transgenic expression of the CRISPR system by suppressing the innate immune response within cells to enhance the gene editing efficiency but also demonstrates a notable tumor inhibitory effect. Based on the specific output expression regulation of CRISPR-CasΦ, we constructed a CRISPR-based gene expression platform, which includes sensor modules for detecting intracellular β-catenin and NF-κB, as well as an SDA module to enhance overall efficiency. In vitro experiments revealed that the CRISPR-based gene expression platform exhibited superior CDK5 expression inhibition efficiency and specific cytotoxicity towards tumor cells. In vitro experiments, we found that CRISPR-based gene expression platforms can selectively kill bladder cancer cells through T cell-mediated cytotoxicity. Our design holds significant assistant potential of transgene therapy and may offer the capability to treat other diseases requiring transgene therapy.

Synthetic biology approaches for improving the specificity and efficacy of cancer immunotherapy

Immunotherapy has shown robust efficacy in treating a broad spectrum of hematological and solid cancers. Despite the transformative impact of immunotherapy on cancer treatment, several outstanding challenges remain. These challenges include on-target off-tumor toxicity, systemic toxicity, and the complexity of achieving potent and sustainable therapeutic efficacy. Synthetic biology has emerged as a promising approach to overcome these obstacles, offering innovative tools for engineering living cells with customized functions. This review provides an overview of the current landscape and future prospects of cancer immunotherapy, particularly emphasizing the role of synthetic biology in augmenting its specificity, controllability, and efficacy. We delineate and discuss two principal synthetic biology strategies: those targeting tumor surface antigens with engineered immune cells and those detecting intratumoral disease signatures with engineered gene circuits. This review concludes with a forward-looking perspective on the enduring challenges in cancer immunotherapy and the potential breakthroughs that synthetic biology may contribute to the field.

Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells

Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.

Logic "AND Gate Circuit"-Based Gasdermin Protein Expressing Nanoplatform Induces Tumor-Specific Pyroptosis to Enhance Cancer Immunotherapy

Pyroptosis mediated by gasdermin protein has shown great potential in cancer immunotherapies. However, the low expression of gasdermin proteins and the systemic toxicity of nonspecific pyroptosis limit its clinical application. Here, we designed a synthetic biology strategy to construct a tumor-specific pyroptosis-inducing nanoplatform M-CNP/Mn@pPHS, in which a pyroptosis-inducing plasmid (pPHS) was loaded onto a manganese (Mn)-doped calcium carbonate nanoparticle and wrapped in a tumor-derived cell membrane. M-CNP/Mn@pPHS showed an efficient tumor targeting ability. After its internalization by tumor cells, the degradation of M-CNP/Mn@pPHS in the acidic endosomal environment allowed the efficient endosomal escape of plasmid pPHS. To trigger tumor-specific pyroptosis, pPHS was designed according to the logic "AND gate circuit" strategy, with Hif-1α and Sox4 as two input signals and gasdermin D induced pyroptosis as output signal. Only in cells with high expression of Hif-1α and Sox4 simultaneously will the output signal gasdermin D be expressed. Since Hif-1α and Sox4 are both specifically expressed in tumor cells, M-CNP/Mn@pPHS induces the tumor-specific expression of gasdermin D and thus pyroptosis, triggering an efficient immune response with little systemic toxicity. The Mn2+ released from the nanoplatform further enhanced the antitumor immune response by stimulating the cGAS-STING pathway. Thus, M-CNP/Mn@pPHS efficiently inhibited tumor growth with 79.8% tumor regression in vivo. We demonstrate that this logic "AND gate circuit"-based gasdermin nanoplatform is a promising strategy for inducing tumor-specific pyroptosis with little systemic toxicity.

A programmable arthritis-specific receptor for guided articular cartilage regenerative medicine

Objective

Investigational cell therapies have been developed as disease-modifying agents for the treatment of osteoarthritis (OA), including those that inducibly respond to inflammatory factors driving OA progression. However, dysregulated inflammatory cascades do not specifically signify the presence of OA. Here, we deploy a synthetic receptor platform that regulates cell behaviors in an arthritis-specific fashion to confine transgene expression to sites characterized by cartilage degeneration.

Methods

An scFv specific for type II collagen (CII) was used to produce a synthetic Notch (synNotch) receptor that enables "CII-synNotch" mesenchymal stromal cells (MSCs) to recognize CII fibers exposed in damaged cartilage. Engineered cell activation by both CII-treated culture surfaces and on primary tissue samples was measured via inducible reporter transgene expression. TGFβ3-expressing cells were assessed for cartilage anabolic gene expression via qRT-PCR. In a co-culture with CII-synNotch MSCs engineered to express IL-1Ra, ATDC5 chondrocytes were stimulated with IL-1α, and inflammatory responses of ATDC5s were profiled via qRT-PCR and an NF-κB reporter assay.

Results

CII-synNotch MSCs are highly responsive to CII, displaying activation ranges over 40-fold in response to physiologic CII inputs. CII-synNotch cells exhibit the capacity to distinguish between healthy and damaged cartilage tissue and constrain transgene expression to regions of exposed CII fibers. Receptor-regulated TGFβ3 expression resulted in upregulation of Acan and Col2a1 in MSCs, and inducible IL-1Ra expression by engineered CII-synNotch MSCs reduced pro-inflammatory gene expression in chondrocytes.

Conclusion

This work demonstrates proof-of-concept that the synNotch platform guides MSCs for spatially regulated, disease-dependent delivery of OA-relevant biologic drugs.

Advancements in synthetic biology-based bacterial cancer therapy: A modular design approach

Synthetic biology aims to program living bacteria cells with artificial genetic circuits for user-defined functions, transforming them into powerful tools with numerous applications in various fields, including oncology. Cancer treatments have serious side effects on patients due to the systemic action of the drugs involved. To address this, new systems that provide localized antitumoral action while minimizing damage to healthy tissues are required. Bacteria, often considered pathogenic agents, have been used as cancer treatments since the early 20th century. Advances in genetic engineering, synthetic biology, microbiology, and oncology have improved bacterial therapies, making them safer and more effective. Here we propose six modules for a successful synthetic biology-based bacterial cancer therapy, the modules include Payload, Release, Tumor-targeting, Biocontainment, Memory, and Genetic Circuit Stability Module. These will ensure antitumor activity, safety for the environment and patient, prevent bacterial colonization, maintain cell stability, and prevent loss or defunctionalization of the genetic circuit.

Spherical nucleic acids-based nanoplatforms for tumor precision medicine and immunotherapy

Precise diagnosis and treatment of tumors currently still face considerable challenges due to the development of highly degreed heterogeneity in the dynamic evolution of tumors. With the rapid development of genomics, personalized diagnosis and treatment using specific genes may be a robust strategy to break through the bottleneck of traditional tumor treatment. Nevertheless, efficient in vivo gene delivery has been frequently hampered by the inherent defects of vectors and various biological barriers. Encouragingly, spherical nucleic acids (SNAs) with good modularity and programmability are excellent candidates capable of addressing traditional gene transfer-associated issues, which enables SNAs a precision nanoplatform with great potential for diverse biomedical applications. In this regard, there have been detailed reviews of SNA in drug delivery, gene regulation, and dermatology treatment. Still, to the best of our knowledge, there is no published systematic review summarizing the use of SNAs in oncology precision medicine and immunotherapy, which are considered new guidelines for oncology treatment. To this end, we summarized the notable advances in SNAs-based precision therapy and immunotherapy for tumors following a classification standard of different types of precise spatiotemporal control on active species by SNAs. Specifically, we focus on the structural diversity and programmability of SNAs. Finally, the challenges and possible solutions were discussed in the concluding remarks. This review will promote the rational design and development of SNAs for tumor-precise medicine and immunotherapy.

Instructional materials that control cellular activity through synthetic Notch receptors

The field of regenerative engineering relies primarily on the dual technical platforms of cell selection/conditioning and biomaterial fabrication to support directed cell differentiation. As the field has matured, an appreciation for the influence of biomaterials on cell behaviors has resulted in engineered matrices that meet biomechanical and biochemical demands of target pathologies. Yet, despite advances in methods to produce designer matrices, regenerative engineers remain unable to reliably orchestrate behaviors of therapeutic cells in situ. Here, we present a platform named MATRIX whereby cellular responses to biomaterials can be custom defined by combining engineered materials with cells expressing cognate synthetic biology control modules. Such privileged channels of material-to-cell communication can activate synthetic Notch receptors and govern activities as diverse as transcriptome engineering, inflammation attenuation, and pluripotent stem cell differentiation, all in response to materials decorated with otherwise bioinert ligands. Further, we show that engineered cellular behaviors are confined to programmed biomaterial surfaces, highlighting the potential to use this platform to spatially organize cellular responses to bulk, soluble factors. This integrated approach of co-engineering cells and biomaterials for orthogonal interactions opens new avenues for reproducible control of cell-based therapies and tissue replacements.

Riskscore Model Based on Oxidative Stress-Related Genes May Facilitate the Prognosis Evaluation for Patients With Colon Cancer

INTRODUCTION

This study aims to identify the oxidative stress-related genes (OSRGs) with prognostic value and develop a riskscore model for prognosis evaluation in colon cancer.

METHODS

The transcriptome data and corresponding clinical information about colon cancer were extracted from The Cancer Genome Atlas database. Differentially expressed OSRGs and transcription factors (TFs) were identified between the normal and tumor samples. A riskscore model was established with OSRGs filtered from Cox regression analysis. This riskscore model was appraised by Kaplan-Meier plot, receiver operating characteristic curve, and Cox regression analysis. The clinical relevance of riskscore and its association with immune cell infiltration were also evaluated.

RESULTS

A total of 307 differentially expressed OSRGs and 64 differential TFs were identified. A TF-OSRG regulatory network was constructed in Cytoscape software. A riskscore model was established based on 17 OSRGs with independent prognostic value. This riskscore model could separate the patients into low-risk and high-risk groups. It also had good predictive ability, with an area under the curve = 0.8. In multivariate Cox regression analysis, age, T stage, and riskscore were identified as independent risk factors in colon cancer. Riskscore was significantly correlated with T stage, N stage, and immune cell infiltration.

DISCUSSION

We established a useful riskscore model with 17 OSRGs for prognosticating the overall survival in patients with colon cancer. This study provides a new insight into the clinical utility of OSRG-based riskscore model, which will hopefully facilitate the prognosis evaluation of patients with colon cancer.

Stable expression of large transgenes via the knock-in of an integrase-deficient lentivirus

The targeted insertion and stable expression of a large genetic payload in primary human cells demands methods that are robust, efficient and easy to implement. Large payload insertion via retroviruses is typically semi-random and hindered by transgene silencing. Leveraging homology-directed repair to place payloads under the control of endogenous essential genes can overcome silencing but often results in low knock-in efficiencies and cytotoxicity. Here we report a method for the knock-in and stable expression of a large payload and for the simultaneous knock-in of two genes at two endogenous loci. The method, which we named CLIP (for 'CRISPR for long-fragment integration via pseudovirus'), leverages an integrase-deficient lentivirus encoding a payload flanked by homology arms and 'cut sites' to insert the payload upstream and in-frame of an endogenous essential gene, followed by the delivery of a CRISPR-associated ribonucleoprotein complex via electroporation. We show that CLIP enables the efficient insertion and stable expression of large payloads and of two difficult-to-express viral antigens in primary T cells at low cytotoxicity. CLIP offers a scalable and efficient method for manufacturing engineered primary cells.

Hydrophobicity Regulation of Energy Acceptors Confined in Mesoporous Silica Enabled Reversible Activation of Optogenetics for Closed-Loop Glycemic Control

Optogenetics-based synthetic biology holds great promise as a cell-based therapy strategy for many clinical incurable diseases; however, precise control over genetic expression strength and timing through disease state-related closed-loop regulation remains a challenge due to the lack of reversible probes to indicate real-time metabolite fluctuations. Here, based on a novel mechanism of analyte-induced hydrophobicity regulation of energy acceptors confined in mesoporous silica, we developed a smart hydrogel platform comprising glucose reversible responsive upconversion nanoprobes and optogenetic engineered cells, in which the upconverted blue light strength was adaptively tuned through blood glucose levels to control optogenetic expressions for insulin secretion. The intelligent hydrogel system enabled convenient maintenance of glycemic homeostasis through simple near-infrared illuminations without any additional glucose concentration monitoring, which efficiently avoided genetic overexpression-induced hypoglycemia. This proof-of-concept strategy efficiently combines diagnostics with optogenetics-based synthetic biology for mellitus therapy, opening up a new avenue for nano-optogenetics.

A synthetic transcription platform for programmable gene expression in mammalian cells

Precise, scalable, and sustainable control of genetic and cellular activities in mammalian cells is key to developing precision therapeutics and smart biomanufacturing. Here we create a highly tunable, modular, versatile CRISPR-based synthetic transcription system for the programmable control of gene expression and cellular phenotypes in mammalian cells. Genetic circuits consisting of well-characterized libraries of guide RNAs, binding motifs of synthetic operators, transcriptional activators, and additional genetic regulatory elements express mammalian genes in a highly predictable and tunable manner. We demonstrate the programmable control of reporter genes episomally and chromosomally, with up to 25-fold more activity than seen with the EF1α promoter, in multiple cell types. We use these circuits to program the secretion of human monoclonal antibodies and to control T-cell effector function marked by interferon-γ production. Antibody titers and interferon-γ concentrations significantly correlate with synthetic promoter strengths, providing a platform for programming gene expression and cellular function in diverse applications.

Synthetic neuromorphic computing in living cells

Computational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.

Engineering the next generation of cell-based therapeutics

Cell-based therapeutics are an emerging modality with the potential to treat many currently intractable diseases through uniquely powerful modes of action. Despite notable recent clinical and commercial successes, cell-based therapies continue to face numerous challenges that limit their widespread translation and commercialization, including identification of the appropriate cell source, generation of a sufficiently viable, potent and safe product that meets patient- and disease-specific needs, and the development of scalable manufacturing processes. These hurdles are being addressed through the use of cutting-edge basic research driven by next-generation engineering approaches, including genome and epigenome editing, synthetic biology and the use of biomaterials.

Versatile tools of synthetic biology applied to drug discovery and production

Although synthetic biology is an emerging research field, which has come to prominence within the last decade, it already has many practical applications. Its applications cover the areas of pharmaceutical biotechnology and drug discovery, bringing essential novel methods and strategies such as metabolic engineering, reprogramming the cell fate, drug production in genetically modified organisms, molecular glues, functional nucleic acids and genome editing. This review discusses the main avenues for synthetic biology application in pharmaceutical biotechnology. The authors believe that synthetic biology will reshape drug development and drug production to a similar extent as the advances in organic chemical synthesis in the 20th century. Therefore, synthetic biology already plays an essential role in pharmaceutical, biotechnology, which is the main focus of this review.

Chemically Modified Poly(A) Analogs Targeting PABP: Structure Activity Relationship and Translation Inhibitory Properties

Poly(A)‐binding protein (PABP) is an essential element of cellular translational machinery. Recent studies have revealed that poly(A) tail modifications can modulate mRNA stability and translational potential, and that oligoadenylate‐derived PABP ligands can act as effective translational inhibitors with potential applications in pain management. Although extensive research has focused on protein‐RNA and protein‐protein interactions involving PABPs, further studies are required to examine the ligand specificity of PABP. In this study, we developed a microscale thermophoresis‐based assay to probe the interactions between PABP and oligoadenylate analogs containing different chemical modifications. Using this method, we evaluated oligoadenylate analogs modified with nucleobase, ribose, and phosphate moieties to identify modification hotspots. In addition, we determined the susceptibility of the modified oligos to CNOT7 to identify those with the potential for increased cellular stability. Consequently, we selected two enzymatically stable oligoadenylate analogs that inhibit translation in rabbit reticulocyte lysates with a higher potency than a previously reported PABP ligand. We believe that the results presented in this study and the implemented methodology can be capitalized upon in the future development of RNA‐based biological tools.

Identification of cell type-specific correlations between ERK activity and cell viability upon treatment with ERK1/2 inhibitors

Increased MAPK signaling is a hallmark of various cancers and is a central regulator of cell survival. Direct ERK1/2 inhibition is considered a promising approach to avoid ERK1/2 reactivation caused by upstream kinases BRAF, MEK1/2, and KRAS, as well as by receptor tyrosine kinase inhibitors, but the dynamics and selectivity of ERK1/2 inhibitors are much less studied compared with BRAF or MEK inhibitors. Using ERK1/2 and downstream kinase ELK1 reporter cell lines of lung cancer (H1299; NRAS^Q61K), colon cancer (HCT-116; KRAS^G13D), neuroblastoma (SH-SY5Y), and leukemia (U937), we examined the relationship between ERK inhibition and drug-induced toxicity for five ERK inhibitors: SCH772984, ravoxertinib, LY3214996, ulixertinib, and VX-11e, as well as one MEK inhibitor, PD0325901. Comparing cell viability and ERK inhibition revealed different ERK dependencies for these cell lines. We identify several drugs, such as SCH772984 and VX-11e, which induce excessive toxicity not directly related to ERK1/2 inhibition in specific cell lines. We also show that PD0325901, LY3214996, and ulixertinib are prone to ERK1/2 reactivation over time. We distinguished two types of ERK1/2 reactivation: the first could be reversed by adding a fresh dose of inhibitors, while the second persists even after additional treatments. We also showed that cells that became resistant to the MEK1/2 inhibitor PD0325901 due to ERK1/2 reactivation remained sensitive to ERK1/2 inhibitor ulixertinib. Our data indicate that correlation of ERK inhibition with drug-induced toxicity in multiple cell lines may help to find more selective and effective ERK1/2 inhibitors.

Synthetic introns enable splicing factor mutation-dependent targeting of cancer cells

Many cancers carry recurrent, change-of-function mutations affecting RNA splicing factors. Here, we describe a method to harness this abnormal splicing activity to drive splicing factor mutation-dependent gene expression to selectively eliminate tumor cells. We engineered synthetic introns that were efficiently spliced in cancer cells bearing SF3B1 mutations, but unspliced in otherwise isogenic wild-type cells, to yield mutation-dependent protein production. A massively parallel screen of 8,878 introns delineated ideal intronic size and mapped elements underlying mutation-dependent splicing. Synthetic introns enabled mutation-dependent expression of herpes simplex virus-thymidine kinase (HSV-TK) and subsequent ganciclovir (GCV)-mediated killing of SF3B1-mutant leukemia, breast cancer, uveal melanoma and pancreatic cancer cells in vitro, while leaving wild-type cells unaffected. Delivery of synthetic intron-containing HSV-TK constructs to leukemia, breast cancer and uveal melanoma cells and GCV treatment in vivo significantly suppressed the growth of these otherwise lethal xenografts and improved mouse host survival. Synthetic introns provide a means to exploit tumor-specific changes in RNA splicing for cancer gene therapy.

Premature translation termination mediated non-ER stress induced ATF6 activation by a ligand-dependent ribosomal frameshifting circuit

The −1 programmed ribosomal frameshifting (−1 PRF) has been explored as a gene regulatory circuit for synthetic biology applications. The −1 PRF usually uses an RNA pseudoknot structure as the frameshifting stimulator. Finding a ligand-responsive pseudoknot with efficient −1 PRF activity is time consuming and is becoming a bottleneck for its development. Inserting a guanine to guanine (GG)–mismatch pair in the 5′-stem of a small frameshifting pseudoknot could attenuate −1 PRF activity by reducing stem stability. Thus, a ligand-responsive frameshifting pseudoknot can be built using GG-mismatch–targeting small molecules to restore stem stability. Here, a pseudoknot requiring stem–loop tertiary interactions for potent frameshifting activity was used as the engineering template. This considerably amplified the effect of mismatch destabilization, and led to creation of a mammalian −1 PRF riboswitch module capable of mediating premature translation termination as a synthetic regulatory mode. Application of the synthetic circuit allowed ligand-dependent ATF6N mimic formation for the activation of protein folding–related genes involved in the unfolded protein response without an ER-stress inducing agent. With the availability of mismatch-targeting molecules, the tailored module thus paves the way for various mismatch plug-ins to streamline highly efficient orthogonal ligand-dependent −1 PRF stimulator development in the synthetic biology toolbox.

Synthetic RNA-based post-transcriptional expression control methods and genetic circuits

RNA-based synthetic genetic circuits provide an alternative for traditional transcription-based circuits in applications where genomic integration is to be avoided. Incorporating various post-transcriptional control methods into such circuits allows for controlling the behaviour of the circuit through the detection of certain biomolecular inputs or reconstituting defined circuit behaviours, thus manipulating cellular functions. In this review, recent developments of various types of post-transcriptional control methods in mammalian cells are discussed as well as auxiliary components that allow for the creation and development of mRNA-based switches. How such post-transcriptional switches are combined into synthetic circuits as well as their applications in biomedical and preclinical settings are also described. Finally, we examine the challenges that need to be surmounted before RNA-based synthetic circuits can be reliably deployed into clinical settings.

Sense-and-Respond Payload Delivery Using a Novel Antigen-Inducible Promoter Improves Suboptimal CAR-T Activation

Chimeric antigen receptor (CAR)-T cell therapies demonstrate the clinical potential of lymphocytes engineered with synthetic properties. However, CAR-T cells are ineffective in most solid tumors, partly due to inadequate activation of the infused lymphocytes at the site of malignancy. To selectively enhance antitumor efficacy without exacerbating off-target toxicities, CAR-T cells can be engineered to preferentially deliver immunostimulatory payloads in tumors. Here, we report a novel antigen-inducible promoter for conditional payload expression in primary human T cells. In therapeutic T cell models, the novel NR4A-based promoter induced higher reporter gene expression than the conventional NFAT-based promoter under weakly immunogenic conditions, where payload expression is most needed. Minimal activity was detected from the inducible promoters in the absence of antigen and after withdrawal of stimulation. As a functional proof-of-concept, we used the NR4A-based promoter to express cytokines in an antimesothelin CAR-T model with suboptimal stimulation and observed improved proliferation compared to T cells engineered with the conventional NFAT promoter or CAR alone. Our system achieves CAR-directed payload expression under weakly immunogenic conditions and could enable the next generation of cell therapies with enhanced antitumor efficacy.

Precise tumor immune rewiring via synthetic CRISPRa circuits gated by concurrent gain/loss of transcription factors

Reinvigoration of antitumor immunity has recently become the central theme for the development of cancer therapies. Nevertheless, the precise delivery of immunotherapeutic activities to the tumors remains challenging. Here, we explore a synthetic gene circuit-based strategy for specific tumor identification, and for subsequently engaging immune activation. By design, these circuits are assembled from two interactive modules, i.e., an oncogenic TF-driven CRISPRa effector, and a corresponding p53-inducible off-switch (NOT gate), which jointly execute an AND-NOT logic for accurate tumor targeting. In particular, two forms of the NOT gate are developed, via the use of an inhibitory sgRNA or an anti-CRISPR protein, with the second form showing a superior performance in gating CRISPRa by p53 loss. Functionally, the optimized AND-NOT logic circuit can empower a highly specific and effective tumor recognition/immune rewiring axis, leading to therapeutic effects in vivo. Taken together, our work presents an adaptable strategy for the development of precisely delivered immunotherapy.

“Reinvigoration of antitumor immunity has recently become the central theme for the development of cancer therapies. Here the authors present an adaptable gene circuit to harness the CRISPRa for tumorlocalized immune activation.”

CRISPR signal conductor 2.0 for redirecting cellular information flow

A key challenge in designing intelligent artificial gene circuits is generating flexible connections between arbitrary components and directly coupling them with endogenous signaling pathways. The CRISPR signal conductor based on conditionally inducible artificial transcriptional regulators can link classic cellular protein signals with targeted gene expression, but there are still problems with multiple signal processing and gene delivery. With the discovery and characterization of new Cas systems and long noncoding RNA (lncRNA) functional motifs, and because of the compatibility of guide RNA with noncoding RNA elements at multiple sites, it is increasingly possible to solve these problems. In this study, we developed CRISPR signal conductor version 2.0 by integrating various lncRNA functional motifs into different parts of the crRNA in the CRISPR-dCasΦ system. This system can directly regulate the expression of target genes by recruiting cellular endogenous transcription factors and efficiently sense a variety of protein signals that are not detected by a classical synthetic system. The new system solved the problems of background leakage and insensitive signaling responses and enabled the construction of logic gates with as many as six input signals, which can be used to specifically target cancer cells. By rewiring endogenous signaling networks, we further demonstrated the effectiveness and biosafety of this system for in vivo cancer gene therapy.

Protease-controlled secretion and display of intercellular signals

To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. If such regulations are at the protein level, there are additional advantages, including compact delivery and direct interactions with endogenous signaling pathways. Here we create a modular, generalizable design called Retained Endoplasmic Cleavable Secretion (RELEASE), with engineered proteins retained in the endoplasmic reticulum and displayed/secreted in response to specific proteases. The design allows functional regulation of multiple synthetic and natural proteins by synthetic protease circuits to realize diverse signal processing capabilities, including logic operation and threshold tuning. By linking RELEASE to additional sensing and processing circuits, we can achieve elevated protein secretion in response to "undruggable" oncogene KRAS mutants. RELEASE should enable the local, programmable delivery of intercellular cues for a broad variety of fields such as neurobiology, cancer immunotherapy and cell transplantation.

Modeling SARS-CoV-2 Infection in Mice Using Lentiviral hACE2 Vectors Infers Two Modes of Immune Responses to SARS-CoV-2 Infection

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a severe global pandemic. Mice models are essential to investigate infection pathology, antiviral drugs, and vaccine development. However, wild-type mice lack the human angiotensin-converting enzyme 2 (hACE2) that mediates SARS-CoV-2 entry into human cells and consequently are not susceptible to SARS-CoV-2 infection. hACE2 transgenic mice could provide an efficient COVID-19 model, but are not always readily available, and practically restricted to specific strains. Therefore, there is a dearth of additional mouse models for SARS-CoV-2 infection. We applied lentiviral vectors to generate hACE2 expression in interferon receptor knock-out (IFNAR1^−/−) mice. Lenti-hACE2 transduction supported SARS-CoV-2 replication in vivo, simulating mild acute lung disease. Gene expression analysis revealed two modes of immune responses to SARS-CoV-2 infection: one in response to the exposure of mouse lungs to SARS-CoV-2 particles in the absence of productive viral replication, and the second in response to productive SARS-CoV-2 infection. Our results infer that immune response to immunogenic elements on incoming virus or in productively infected cells stimulate diverse immune effectors, even in absence of type I IFN signaling. Our findings should contribute to a better understanding of the immune response triggered by SARS-CoV-2 and to further elucidate COVID-19.

An AAV gene therapy computes over multiple cellular inputs to enable precise targeting of multifocal hepatocellular carcinoma in mice

[Figure: see text].

Implementing Logic Gates for Safer Immunotherapy of Cancer

Targeting solid tumors with absolute precision is a long-standing challenge in cancer immunotherapy. The identification of antigens, which are expressed by a large fraction of tumors of a given type and, preferably, across various types, but not by normal cells, holds the key to developing safe, off-the-shelf immunotherapies. Although the quest for widely shared, strictly tumor-specific antigens has been the focus of tremendous effort, only few such candidates have been implicated. Almost all antigens that are currently explored as targets for chimeric antigen receptor (CAR) or T cell receptor (TCR)-T cell therapy are also expressed by healthy cells and the risk of on-target off-tumor toxicity has remained a major concern. Recent studies suggest that this risk could be obviated by targeting instead combinations of two or more antigens, which are co-expressed by tumor but not normal cells and, as such, are tumor-specific. Moreover, the expression of a shared tumor antigen along with the lack of a second antigen that is expressed by normal tissues can also be exploited for precise recognition. Additional cues, antigenic or non-antigenic ones, which characterize the tumor microenvironment, could be harnessed to further increase precision. This review focuses on attempts to define the targetable signatures of tumors and assesses different strategies employing advanced synthetic biology for translating such information into safer modes of immunotherapy, implementing the principles of Boolean logic gates.

Engineering living therapeutics with synthetic biology

The steadfast advance of the synthetic biology field has enabled scientists to use genetically engineered cells, instead of small molecules or biologics, as the basis for the development of novel therapeutics. Cells endowed with synthetic gene circuits can control the localization, timing and dosage of therapeutic activities in response to specific disease biomarkers and thus represent a powerful new weapon in the fight against disease. Here, we conceptualize how synthetic biology approaches can be applied to programme living cells with therapeutic functions and discuss the advantages that they offer over conventional therapies in terms of flexibility, specificity and predictability, as well as challenges for their development. We present notable advances in the creation of engineered cells that harbour synthetic gene circuits capable of biological sensing and computation of signals derived from intracellular or extracellular biomarkers. We categorize and describe these developments based on the cell scaffold (human or microbial) and the site at which the engineered cell exerts its therapeutic function within its human host. The design of cell-based therapeutics with synthetic biology is a rapidly growing strategy in medicine that holds great promise for the development of effective treatments for a wide variety of human diseases.

Synthetic Circuit-Driven Expression of Heterologous Enzymes for Disease Detection

The integration of nanotechnology and synthetic biology could lay the framework for new classes of engineered biosensors that produce amplified readouts of disease states. As a proof-of-concept demonstration of this vision, here we present an engineered gene circuit that, in response to cancer-associated transcriptional deregulation, expresses heterologous enzyme biomarkers whose activity can be measured by nanoparticle sensors that generate amplified detection readouts. Specifically, we designed an AND-gate gene circuit that integrates the activity of two ovarian cancer-specific synthetic promoters to drive the expression of a heterologous protein output, secreted Tobacco Etch Virus (TEV) protease, exclusively from within tumor cells. Nanoparticle probes were engineered to carry a TEV-specific peptide substrate in order to measure the activity of the circuit-generated enzyme to yield amplified detection signals measurable in the urine or blood. We applied our integrated sense-and-respond system in a mouse model of disseminated ovarian cancer, where we demonstrated measurement of circuit-specific TEV protease activity both in vivo using exogenously administered nanoparticle sensors and ex vivo using quenched fluorescent probes. We envision that this work will lay the foundation for how synthetic biology and nanotechnology can be meaningfully integrated to achieve next-generation engineered biosensors.

Nanotechnology-Assisted RNA Delivery: From Nucleic Acid Therapeutics to COVID-19 Vaccines

In recent years, the main quest of science has been the pioneering of the groundbreaking biomedical strategies needed for achieving a personalized medicine. Ribonucleic acids (RNAs) are outstanding bioactive macromolecules identified as pivotal actors in regulating a wide range of biochemical pathways. The ability to intimately control the cell fate and tissue activities makes RNA-based drugs the most fascinating family of bioactive agents. However, achieving a widespread application of RNA therapeutics in humans is still a challenging feat, due to both the instability of naked RNA and the presence of biological barriers aimed at hindering the entrance of RNA into cells. Recently, material scientists' enormous efforts have led to the development of various classes of nanostructured carriers customized to overcome these limitations. This work systematically reviews the current advances in developing the next generation of drugs based on nanotechnology-assisted RNA delivery. The features of the most used RNA molecules are presented, together with the development strategies and properties of nanostructured vehicles. Also provided is an in-depth overview of various therapeutic applications of the presented systems, including coronavirus disease vaccines and the newest trends in the field. Lastly, emerging challenges and future perspectives for nanotechnology-mediated RNA therapies are discussed.

Gene-circuit therapy on the horizon: synthetic biology tools for engineered therapeutics

Therapeutic genome modification requires precise control over the introduced therapeutic functions. Current approaches of gene and cell therapy fail to deliver such command and rely on semi-quantitative methods with limited influence on timing, contextuality and levels of transgene expression, and hence on therapeutic function. Synthetic biology offers new opportunities for quantitative functionality in designing therapeutic systems and their components. Here, we discuss synthetic biology tools in their therapeutic context, with examples of proof-of-principle and clinical applications of engineered synthetic biomolecules and higher-order functional systems, i.e. gene circuits. We also present the prospects of future development towards advanced gene-circuit therapy.

Cytotoxic Marine Alkaloid 3,10-Dibromofascaplysin Induces Apoptosis and Synergizes with Cytarabine Resulting in Leukemia Cell Death

Myeloid leukemia is a hematologic neoplasia characterized by a clonal proliferation of hematopoietic stem cell progenitors. Patient prognosis varies depending on the subtype of leukemia as well as eligibility for intensive treatment regimens and allogeneic stem cell transplantation. Although significant progress has been made in the therapy of patients including novel targeted treatment approaches, there is still an urgent need to optimize treatment outcome. The most common therapy is based on the use of chemotherapeutics cytarabine and anthrayclines. Here, we studied the effect of the recently synthesized marine alkaloid 3,10-dibromofascaplysin (DBF) in myeloid leukemia cells. Unsubstituted fascaplysin was early found to affect cell cycle via inhibiting CDK4/6, thus we compared the activity of DBF and other brominated derivatives with known CDK4/6 inhibitor palbociclib, which was earlier shown to be a promising candidate to treat leukemia. Unexpectedly, the effect DBF on cell cycle differs from palbociclib. In fact, DBF induced leukemic cells apoptosis and decreased the expression of genes responsible for cancer cell survival. Simultaneously, DBF was found to activate the E2F1 transcription factor. Using bioinformatical approaches we evaluated the possible molecular mechanisms, which may be associated with DBF-induced activation of E2F1. Finally, we found that DBF synergistically increase the cytotoxic effect of cytarabine in different myeloid leukemia cell lines. In conclusion, DBF is a promising drug candidate, which may be used in combinational therapeutics approaches to reduce leukemia cell growth.

Engineering genetic devices for in vivo control of therapeutic T cell activity triggered by the dietary molecule resveratrol

Chimeric antigen receptor (CAR)-engineered T cell therapies have been recognized as powerful strategies in cancer immunotherapy; however, the clinical application of CAR-T is currently constrained by severe adverse effects in patients, caused by excessive cytotoxic activity and poor T cell control. Herein, we harnessed a dietary molecule resveratrol (RES)-responsive transactivator and a transrepressor to develop a repressible transgene expression (RESrep) device and an inducible transgene expression (RESind) device, respectively. After optimization, these tools enabled the control of CAR expression and CAR-mediated antitumor function in engineered human cells. We demonstrated that a resveratrol-repressible CAR expression (RESrep-CAR) device can effectively inhibit T cell activation upon resveratrol administration in primary T cells and a xenograft tumor mouse model. Additionally, we exhibit how a resveratrol-inducible CAR expression (RESind-CAR) device can achieve fine-tuned and reversible control over T cell activation via a resveratrol-titratable mechanism. Furthermore, our results revealed that the presence of RES can activate RESind-CAR T cells with strong anticancer cytotoxicity against cells in vitro and in vivo. Our study demonstrates the utility of RESrep and RESind devices as effective tools for transgene expression and illustrates the potential of RESrep-CAR and RESind-CAR devices to enhance patient safety in precision cancer immunotherapies.

Design and Evaluation of Synthetic RNA-Based Incoherent Feed-Forward Loop Circuits

RNA-based regulators are promising tools for building synthetic biological systems that provide a powerful platform for achieving a complex regulation of transcription and translation. Recently, de novo-designed synthetic RNA regulators, such as the small transcriptional activating RNA (STAR), toehold switch (THS), and three-way junction (3WJ) repressor, have been utilized to construct RNA-based synthetic gene circuits in living cells. In this work, we utilized these regulators to construct type 1 incoherent feed-forward loop (IFFL) circuits in vivo and explored their dynamic behaviors. A combination of a STAR and 3WJ repressor was used to construct an RNA-only IFFL circuit. However, due to the fast kinetics of RNA–RNA interactions, there was no significant timescale difference between the direct activation and the indirect inhibition, that no pulse was observed in the experiments. These findings were confirmed with mechanistic modeling and simulation results for a wider range of conditions. To increase delay in the inhibition pathway, we introduced a protein synthesis process to the circuit and designed an RNA–protein hybrid IFFL circuit using THS and TetR protein. Simulation results indicated that pulse generation could be achieved with this RNA–protein hybrid model, and this was further verified with experimental realization in E. coli. Our findings demonstrate that while RNA-based regulators excel in speed as compared to protein-based regulators, the fast reaction kinetics of RNA-based regulators could also undermine the functionality of a circuit (e.g., lack of significant timescale difference). The agreement between experiments and simulations suggests that the mechanistic modeling can help debug issues and validate the hypothesis in designing a new circuit. Moreover, the applicability of the kinetic parameters extracted from the RNA-only circuit to the RNA–protein hybrid circuit also indicates the modularity of RNA-based regulators when used in a different context. We anticipate the findings of this work to guide the future design of gene circuits that rely heavily on the dynamics of RNA-based regulators, in terms of both modeling and experimental realization.

Cell Fate Reprogramming in the Era of Cancer Immunotherapy

Advances in understanding how cancer cells interact with the immune system allowed the development of immunotherapeutic strategies, harnessing patients' immune system to fight cancer. Dendritic cell-based vaccines are being explored to reactivate anti-tumor adaptive immunity. Immune checkpoint inhibitors and chimeric antigen receptor T-cells (CAR T) were however the main approaches that catapulted the therapeutic success of immunotherapy. Despite their success across a broad range of human cancers, many challenges remain for basic understanding and clinical progress as only a minority of patients benefit from immunotherapy. In addition, cellular immunotherapies face important limitations imposed by the availability and quality of immune cells isolated from donors. Cell fate reprogramming is offering interesting alternatives to meet these challenges. Induced pluripotent stem cell (iPSC) technology not only enables studying immune cell specification but also serves as a platform for the differentiation of a myriad of clinically useful immune cells including T-cells, NK cells, or monocytes at scale. Moreover, the utilization of iPSCs allows introduction of genetic modifications and generation of T/NK cells with enhanced anti-tumor properties. Immune cells, such as macrophages and dendritic cells, can also be generated by direct cellular reprogramming employing lineage-specific master regulators bypassing the pluripotent stage. Thus, the cellular reprogramming toolbox is now providing the means to address the potential of patient-tailored immune cell types for cancer immunotherapy. In parallel, development of viral vectors for gene delivery has opened the door for in vivo reprogramming in regenerative medicine, an elegant strategy circumventing the current limitations of in vitro cell manipulation. An analogous paradigm has been recently developed in cancer immunotherapy by the generation of CAR T-cells in vivo. These new ideas on endogenous reprogramming, cross-fertilized from the fields of regenerative medicine and gene therapy, are opening exciting avenues for direct modulation of immune or tumor cells in situ, widening our strategies to remove cancer immunotherapy roadblocks. Here, we review current strategies for cancer immunotherapy, summarize technologies for generation of immune cells by cell fate reprogramming as well as highlight the future potential of inducing these unique cell identities in vivo, providing new and exciting tools for the fast-paced field of cancer immunotherapy.

Identification and Validation of Immune Molecular Subtypes in Pancreatic Ductal Adenocarcinoma: Implications for Prognosis and Immunotherapy

Background

Pancreatic ductal adenocarcinoma (PDAC) remains treatment refractory. Immunotherapy has achieved success in the treatment of multiple malignancies. However, the efficacy of immunotherapy in PDAC is limited by a lack of promising biomarkers. In this research, we aimed to identify robust immune molecular subtypes of PDAC to facilitate prognosis prediction and patient selection for immunotherapy.

Methods

A training cohort of 149 PDAC samples from The Cancer Genome Atlas (TCGA) with mRNA expression data was analyzed. By means of non-negative matrix factorization (NMF), we virtually dissected the immune-related signals from bulk gene expression data. Detailed immunogenomic and survival analyses of the immune molecular subtypes were conducted to determine their biological and clinical relevance. Validation was performed in five independent datasets on a total of 615 samples.

Results

Approximately 31% of PDAC samples (46/149) had higher immune cell infiltration, more active immune cytolytic activity, higher activation of the interferon pathway, a higher tumor mutational burden (TMB), and fewer copy number alterations (CNAs) than the other samples (all P < 0.001). This new molecular subtype was named Immune Class, which served as an independent favorable prognostic factor for overall survival (hazard ratio, 0.56; 95% confidence interval, 0.33-0.97). Immune Class in cooperation with previously reported tumor and stroma classifications had a cumulative effect on PDAC prognostic stratification. Moreover, programmed cell death-1 (PD-1) inhibitors showed potential efficacy for Immune Class (P = 0.04). The robustness of our immune molecular subtypes was further verified in the validation cohort.

Conclusions

By capturing immune-related signals in the PDAC tumor microenvironment, we reveal a novel molecular subtype, Immune Class. Immune Class serves as an independent favorable prognostic factor for overall survival in PDAC patients.

Topologies of synthetic gene circuit for optimal fold change activation

Computations widely exist in biological systems for functional regulations. Recently, incoherent feedforward loop and integral feedback controller have been implemented into Escherichia coli to achieve a robust adaptation. Here, we demonstrate that an indirect coherent feedforward loop and mutual inhibition designs can experimentally improve the fold change of promoters, by reducing the basal level while keeping the maximum activity high. We applied both designs to six different promoters in E. coli, starting with synthetic inducible promoters as a proof-of-principle. Then, we examined native promoters that are either functionally specific or systemically involved in complex pathways such as oxidative stress and SOS response. Both designs include a cascade having a repressor and a construct of either transcriptional interference or antisense transcription. In all six promoters, an improvement of up to ten times in the fold change activation was observed. Theoretically, our unitless models show that when regulation strength matches promoter basal level, an optimal fold change can be achieved. We expect that this methodology can be applied in various biological systems for biotechnology and therapeutic applications.

Cell-Free Characterization of Coherent Feed-Forward Loop-Based Synthetic Genetic Circuits

Regulatory pathways inside living cells employ feed-forward architectures to fulfill essential signal processing functions that aid in the interpretation of various types of inputs through noise-filtering, fold-change detection and adaptation. Although it has been demonstrated computationally that a coherent feed-forward loop (CFFL) can function as noise filter, a property essential to decoding complex temporal signals, this motif has not been extensively characterized experimentally or integrated into larger networks. Here we use post-transcriptional regulation to implement and characterize a synthetic CFFL in an Escherichia coli cell-free transcription-translation system and build larger composite feed-forward architectures. We employ microfluidic flow reactors to probe the response of the CFFL circuit using both persistent and short, noise-like inputs and analyze the influence of different circuit components on the steady-state and dynamics of the output. We demonstrate that our synthetic CFFL implementation can reliably repress background activity compared to a reference circuit, but displays low potential as a temporal filter, and validate these findings using a computational model. Our results offer practical insight into the putative noise-filtering behavior of CFFLs and show that this motif can be used to mitigate leakage and increase the fold-change of the output of synthetic genetic circuits.

Synthetic and systems biology principles in the design of programmable oncolytic virus immunotherapies for glioblastoma

Oncolytic viruses (OVs) are a class of immunotherapeutic agents with promising preclinical results for the treatment of glioblastoma (GBM) but have shown limited success in recent clinical trials. Advanced bioengineering principles from disciplines such as synthetic and systems biology are needed to overcome the current challenges faced in developing effective OV-based immunotherapies for GBMs, including off-target effects and poor clinical responses. Synthetic biology is an emerging field that focuses on the development of synthetic DNA constructs that encode networks of genes and proteins (synthetic genetic circuits) to perform novel functions, whereas systems biology is an analytical framework that enables the study of complex interactions between host pathways and these synthetic genetic circuits. In this review, the authors summarize synthetic and systems biology concepts for developing programmable, logic-based OVs to treat GBMs. Programmable OVs can increase selectivity for tumor cells and enhance the local immunological response using synthetic genetic circuits. The authors discuss key principles for developing programmable OV-based immunotherapies, including how to 1) select an appropriate chassis, a vector that carries a synthetic genetic circuit, and 2) design a synthetic genetic circuit that can be programmed to sense key signals in the GBM microenvironment and trigger release of a therapeutic payload. To illustrate these principles, some original laboratory data are included, highlighting the need for systems biology studies, as well as some preliminary network analyses in preparation for synthetic biology applications. Examples from the literature of state-of-the-art synthetic genetic circuits that can be packaged into leading candidate OV chassis are also surveyed and discussed.

Development of a multi-gene-based immune prognostic signature in ovarian Cancer

Background

Various components of the immune system play a critical role in the prognosis and treatment response in ovarian cancer (OC). Immunotherapy has been recognized as a hallmark of cancer but the effect is contradictional. Reliable immune gene-based prognostic biomarkers or regulatory factors are necessary to be systematically explored to develop an individualized prediction signature.

Methods

This study systematically explored the gene expression profiles in patients with ovarian cancer from RNA-seq data set for The Cancer Genome Atlas (TCGA). Differentially expressed immune genes and transcription factors (TFs) were identified using the collected immune genes from ImmPort dataset and TFs from Cistoma database. Survival associated immune genes and TFs were identified in terms of overall survival. The prognostic signature was developed based on survival associated immune genes with LASSO (Least absolute shrinkage and selection operator) Cox regression analysis. Further, we performed network analysis to uncover the potential regulators of immune-related genes with the help of computational biology.

Results

The prognostic signature, a weighted combination of the 21 immune-related genes, performed moderately in survival prediction with AUC was 0.746, 0.735, and 0.749 for 1, 3, and 5 year overall survival, respectively. Network analysis uncovered the regulatory role of TFs in immune genes. Intriguingly, the prognostic signature reflected the immune cells landscape and infiltration of some immune cell subtypes.

Conclusions

We first constructed a signature with 21 immune genes of clinical significance, which showed promising predictive value in the surveillance, and prognosis of OC patients.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13048-021-00766-4.

Tumor-tagging by oncolytic viruses: A novel strategy for CAR-T therapy against solid tumors

Chimeric antigen receptor (CAR) T cell therapy is one of the most promising immunotherapies in the past decade. It brings hope for cure to patients with previously refractory hematological malignancies. However, when translating this strategy into non-hematologic malignancies, the antitumor activity from multiple clinical studies seemed to be subtle or transient. The less satisfying efficacy in solid tumors might at least due to antigen heterogeneity, suboptimal CAR-T cell trafficking and tumor immunosuppressive environment. Here, we will review the updating strategies to challenge the therapeutic impediments of CAR-T therapy in non-hematologic malignancies. We mainly focus on the combination with oncolytic viruses (OV), the born allies for CAR-T cells. In addition to previously reported OVs-arming strategy, we discuss recently proposed tumor-tagging concept by OVs as CAR-T targets, as well as the possible improvements. Overall, tumor-tagging strategy by OVs combination with CAR-T would be a novel and promising solution for the heterogeneity and immunosuppressive microenvironment of solid tumors.

A Parallel Approach to Perform Threshold Value and Propagation Delay Analyses of Genetic Logic Circuit Models

Experiments with synthetic genetic logic circuits can be time-consuming and expensive. Accordingly, advances in the field of computer-aided design and simulation of genetic circuits have reduced the cost and time required for experimentation. D-VASim is the first genetic circuit simulation tool that allows users to interact with the model during run-time. In contrast to electronic circuits, genetic circuits have different threshold values for different circuits, which need to be estimated prior to simulation. D-VASim allows the user to perform threshold concentration and propagation delay analysis before simulating the circuit. The algorithm currently used in D-VASim has considerable scope for improvements. Thus, we propose a parallel implementation of the algorithm, significantly faster by up to 16 times. In adddition, we improve the algorithm for consistent runtimes across multiple simulation runs under the same parameter settings, reducing the worst-case standard deviation in runtime from 6.637 to 1.841. Our algorithm also estimates the threshold value more accurately, as evident from experimentation for long runtimes. With these modifications, the utility of D-VASim as a virtual laboratory environment has been significantly enhanced.

Precision Tools in Immuno-Oncology: Synthetic Gene Circuits for Cancer Immunotherapy

Engineered mammalian cells for medical purposes are becoming a clinically relevant reality thanks to advances in synthetic biology that allow enhanced reliability and safety of cell-based therapies. However, their application is still hampered by challenges including time-consuming design-and-test cycle iterations and costs. For example, in the field of cancer immunotherapy, CAR-T cells targeting CD19 have already been clinically approved to treat several types of leukemia, but their use in the context of solid tumors is still quite inefficient, with additional issues related to the adequate quality control for clinical use. These limitations can be overtaken by innovative bioengineering approaches currently in development. Here we present an overview of recent synthetic biology strategies for mammalian cell therapies, with a special focus on the genetic engineering improvements on CAR-T cells, discussing scenarios for the next generation of genetic circuits for cancer immunotherapy.

Defining the Teratoma as a Model for Multi-lineage Human Development

We propose that the teratoma, a recognized standard for validating pluripotency in stem cells, could be a promising platform for studying human developmental processes. Performing single-cell RNA sequencing (RNA-seq) of 179,632 cells across 23 teratomas from 4 cell lines, we found that teratomas reproducibly contain approximately 20 cell types across all 3 germ layers, that inter-teratoma cell type heterogeneity is comparable with organoid systems, and teratoma gut and brain cell types correspond well to similar fetal cell types. Furthermore, cellular barcoding confirmed that injected stem cells robustly engraft and contribute to all lineages. Using pooled CRISPR-Cas9 knockout screens, we showed that teratomas can enable simultaneous assaying of the effects of genetic perturbations across all germ layers. Additionally, we demonstrated that teratomas can be sculpted molecularly via microRNA (miRNA)-regulated suicide gene expression to enrich for specific tissues. Taken together, teratomas are a promising platform for modeling multi-lineage development, pan-tissue functional genetic screening, and tissue engineering.

Engineering precision therapies: lessons and motivations from the clinic

In the past decade, gene- and cell-based therapies have been at the forefront of the biomedical revolution. Synthetic biology, the engineering discipline of building sophisticated ‘genetic software’ to enable precise regulation of gene activities in living cells, has been a decisive success factor of these new therapies. Here, we discuss the core technologies and treatment strategies that have already gained approval for therapeutic applications in humans. We also review promising preclinical work that could either enhance the efficacy of existing treatment strategies or pave the way for new precision medicines to treat currently intractable human conditions.

Synthesizing AND gate minigene circuits based on CRISPReader for identification of bladder cancer cells

The logical AND gate gene circuit based on the CRISPR-Cas9 system can distinguish bladder cancer cells from normal bladder epithelial cells. However, the layered artificial gene circuits have the problems of high complexity, difficulty in accurately predicting the behavior, and excessive redundancy, which cannot be applied to clinical translation. Here, we construct minigene circuits based on the CRISPReader, a technology used to control promoter-less gene expression in a robust manner. The minigene circuits significantly induce robust gene expression output in bladder cancer cells, but have nearly undetectable gene expression in normal bladder epithelial cells. The minigene circuits show a higher capability for cancer identification and intervention when compared with traditional gene circuits, and could be used for in vivo cancer gene therapy using the all-in-one AAV vector. This approach expands the design ideas and concepts of gene circuits in medical synthetic biology.